evaluating climate change impacts: an integrated approach

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Evaluating Climate Evaluating Climate Change Impacts:Change Impacts:an Integrated Approach an Integrated Approach

Marco Lazzarin and Francesco Bosello

Trieste, 09/07/03

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output Temperature level

Temperature change

+

Other (e.g. precip.)

Inputs forVegetationVegetation

Sea LevelSea Level

WaterWater

AgricultureAgriculture

En

vir.

Im

pac

t M

odu

les

En

vir.

Im

pac

t M

odu

les

Interface(s) translating env.

impacts in changes in key

economic variables

in stocks (K,L,La,NR)

in productivity

GHGs emissions

Economic ValuationCGE

GCM

Evaluating Climate Change Impacts: an Integrated ApproachEvaluating Climate Change Impacts: an Integrated Approach

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Steps to conduct the exerciseSteps to conduct the exercise

1. Take an economic model sufficiently disaggregated. (Simplified but good enough representation of the economic system).

2. Build a baseline for the future “without climate change”.

3. Over-impose to the baseline shocks in key economic variables induced by climate change.

4. Comment results.


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Our CGE Economic ModelOur CGE Economic Model

GTAP (Global Trade Analysis Project) is a database (66 regions, 57 sectors) but also a global comparative static applied general equilibrium model calibrated in 1997

The GTAP system of equations is based on microeconomic foundations providing a detailed specification of household and firm behaviour within individual regions and trade linkages between regions.

• Hertel, T.W., (1996) Global Trade Analysis: Modelling and applications, Cambridge University Press.

• www.gtap.org


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• GTAP-E: extended by Burniaux and Truong (2001) in order to account for an environmental part (CO2 emissions); version 8 8.

• GTAP-EX: our developed version of the model, by augmenting the industrial disaggregation, especially in the agricultural sector; version 8 17.


Our CGE Economic ModelOur CGE Economic Model

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Regional and sectoral mapping Regional and sectoral mapping of GTAP-EXof GTAP-EX

Regions:Regions:

USA: USA: United States United StatesEU: EU: European Union European UnionEEFSU: EEFSU: Eastern Europe and Former Eastern Europe and Former

Soviet UnionSoviet UnionJPN: JPN: Japan JapanRoA1: RoA1: Oth. Annex 1 countries Oth. Annex 1 countriesEex: Eex: Net Energy Exporters Net Energy ExportersCHIND: CHIND: China and India China and IndiaRoW: RoW: Rest of the World Rest of the World

Sectors:Sectors:

RiceRiceWheatWheatCereal CropsCereal CropsVegetable FruitsVegetable FruitsAnimalsAnimalsForestryForestryFishingFishingCoalCoalOilOilGasGasOil ProductsOil ProductsElectricityElectricityWaterWaterEnergy Intensive industriesEnergy Intensive industriesOther industriesOther industriesMarket ServicesMarket ServicesNon-Market ServicesNon-Market Services


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The baseline construction processThe baseline construction process

Construction of baseline “without climate change” for the future selecting relevant years (2010, 2030, 2050) and “re-calibrating” the model using:

• projected data from G-Cubed model (McKibbin, 1999) for stocks of capital, labour, population and related productivity

• IMAGE (RIVM 2001) for land productivity.

• McKibbin, W.J, Wilcoxen, P.J., (1998) The Theoretical and Empirical Structure of the GCubed Model, Economic Modelling, vol. 16(1)

• IMAGE (2001), The IMAGE 2.2 Implementation of the SRES Scenarios, RIVM CDROM, Bilthoven, The Netherlands.


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Modelling the Modelling the impactsimpacts

Tol (2002) reviews the available studies for impacts on human health, productivity in agriculture and forestry, losses of species and ecosystems, sea level rise, energy consumption and water resources.

He discusses methodological issues and provides a meta-analysis, obtaining “best guesses” for the valuation of the various impacts

• Tol, R.S.J.,(2002) Estimates the Damage Costs of Climate Change: Benchmark and Dynamic Estimates, Part I and II, Environmental and Resources Economics, vol. 21.


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Implementing Climate-Change Implementing Climate-Change Impacts on Health in GTAP-EXImpacts on Health in GTAP-EX


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• Climate change affects human health in several ways. Here we consider the influence of climate change on heat and cold stress related diseases (respiratory and cardiovascular), and on main Vector-borne diseases (malaria, dengue and schistosomiasis).

• Cardiovascular and respiratory disorders are worsened by both extreme cold and extreme hot weather and are mainly an urban phenomenon that affect differently people above and below 65 years old. Vector-borne diseases may intensify and spread with warmer and more humid conditions.

• At this preliminary stage the main economic effect of the changes in health status that we consider are changes in labour productivity. In particular the change in labour productivity per year is related via statistical model to the total number of life years diseased due to the change in the incidence of the above mentioned illness.

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Nature of inputs:

Labour productivity loss due to 1°C or 2°C temperature increase respect to 2000 per country (all).

Steps for implementation:

(a) Compute emission pattern starting from data for 2010, 2030, 2050.

(b) Compute temperature increase respect to 2000 according to that pattern in 2010, 2030, 2050.

(c) Re-scaling labour productivity losses.

(d) Aggregate losses according to GTAP-EX 8 world regions.

(e) Shock the GTAP-EX system.


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CO2 EmissionsCO2 Emissions (Giga Ton of C)(Giga Ton of C)

0

5

10

15

20

25

30

35

2000 2010 2020 2030 2040 2050

GT

C


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Estimated Temperature IncreaseEstimated Temperature Increase

Year

Temperatureincrease w.r.t.Pre-industrial

level

Variation w.r.t.2000

2000 0.491 0.00002010 0.494 0.00292020 0.659 0.16782030 0.859 0.36792040 1.114 0.62292050 1.425 0.9342


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Labour productivity loss due to Labour productivity loss due to climate changeclimate change

Percentage changes respect to 2010, 2030 and 2050 baselines.

Aggregated according to GTAP-EX macro-regions.

These are the shocks to labour productivity direct inputsinputs for GTAP-EX

Labour productivity loss due to climate changeUSA EU EEFSU JPN RoA1 EEx CHIND RoW

2010 0.000011 0.000056 0.000038 -0.000001 0.00005 -0.000198 -0.000146 -0.0001622030 0.001904 0.009999 0.00675 -0.000092 0.009073 -0.035665 -0.026335 -0.0291862050 0.004919 0.025832 0.017438 -0.000238 0.023439 -0.092135 -0.068033 -0.075397


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• We can note firstly that the changes in productivity are quite small, for example maximum shock is smaller than 0.1%

• We can note that these impacts are both positive and negative. In particular they are positive (increased productivity) for developed regions (except JPN) whereas they are negative for the developing world. This is due to the fact that major labour productivity losses are induced by vector-borne diseases, that are in practice equal to zero in the developed countries.

• interesting is the case of JPN where cardiovascular and respiratory diseases worsen decreasing labour productivity. This effect that is a counter tendency for developed regions is due to the high percentage and density of population living in urban areas.

Labour productivity loss due to Labour productivity loss due to climate change: some commentsclimate change: some comments

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Climate change impacts on health:Climate change impacts on health:selected results selected results

Equivalent Variation (1997million US $ respect to the baseline)USA EU EEFSU JPN RoA1 EEx CHIND RoW

2010 0.663518 3.354671 0.290912 -0.038018 0.588743 -3.600199 -1.395034 -3.5193992030 191.8071 952.384 89.24757 -9.530933 167.5813 -1063.246 -423.2907 -1092.2662050 848.296 3539.161 359.0927 -66.77731 600.8062 -3986.771 -1313.981 -4124.344

GDP (quantity index - percentage change respect to the baseline)USA EU EEFSU JPN RoA1 EEx CHIND RoW

2010 0.000007 0.000032 0.000022 0.000000 0.00003 -0.000093 -0.000077 -0.0000822030 0.001221 0.005814 0.004074 -0.000051 0.00555 -0.016981 -0.013402 -0.0151922050 0.003197 0.015026 0.010328 -0.00022 0.01421 -0.040966 -0.024957 -0.036528

CO2 Emissions (percentage change respect to the baselines)USA EU EEFSU JPN RoA1 EEx CHIND RoW

2010 0.000007 0.00002 0.00001 0.000005 0.000017 -0.000043 -0.000029 -0.000032030 0.001087 0.003516 0.001905 0.000728 0.002962 -0.007823 -0.005406 -0.0055762050 0.000868 0.006073 0.004342 -0.004509 0.005179 -0.01976 -0.010447 -0.0134


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Climate change impacts on health:Climate change impacts on health:comments comments

1. EV is a welfare indicator: “Equivalent variation is the compensating payment that in the absence of the economic change moves the consumer to the welfare level associated with the change. For example, if we have a price increase, the equivalent variation is the maximum amount the consumer would be willing to pay to avoid the price increase.”

2. It is possible to note that negative shocks on labour productivity translate in negative impacts on GDP and welfare and vice-versa. The same is true for emission: in general a lower GDP implies lower emission…

3. …Again is interesting the case of Japan: in 2030 the variation of GDP respect to the baseline is negative whereas variation of emissions from the baselines are positive. This is a typical effects that a CGE model can highlight: a substitution process between production factor. In this specific case labour is substituted with capital and, as a consequence, even though output declines the production mix is nevertheless more polluting.

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Implementing Climate-Change Impacts Implementing Climate-Change Impacts on Sea Level Rise in GTAP-EXon Sea Level Rise in GTAP-EX


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Nature of inputs:

Dry-land loss fraction without coastal protection due to 5, 15, 25 cm of sea level rise estimated for 2010, 2030 and 2050 respectively

Steps for implementation:

(a) Aggregate losses according to GTAP-EX 8 world regions.

(b) Shock the GTAP-EX system.


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Re- scaled dryland loss due toRe- scaled dryland loss due tosea-level risesea-level rise

Percentage changes respect to 2010, 2030 and 2050 baselines.

Aggregation according to GTAP-EX macro-regions.

These are the shocks to stock of land direct inputs for GTAP-EX

Re-scaled dryland loss due to sea level riseUSA EU EEFSU JPN RoA1 EEx CHIND RoW

2010 -0.01092 -0.00648 -0.00366 -0.03069 -0.00121 -0.03673 -0.01659 -0.030242030 -0.03275 -0.01945 -0.01098 -0.09206 -0.00364 -0.11019 -0.04976 -0.090712050 -0.05459 -0.03242 -0.0183 -0.15344 -0.00606 -0.18366 -0.08293 -0.15118


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Impact of climate-change induced Impact of climate-change induced sea-level rise: selected resultssea-level rise: selected results


2010 -1.048711 -1.43142 -0.401172 -0.428043 -0.038618 -7.260132 -2.64881 -4.1534442030 -41.92249 -43.82682 -8.733319 -2.39755 3.909041 -134.392 -83.41387 -97.012922050 -1609.616 -1277.251 -203.6237 150.337 285.1913 -1352.669 -1296.328 -1349.962


2010 0.000102 0.000121 0.000068 0.000123 0.000116 -0.000134 -0.000065 -0.0000332030 0.001384 0.001556 0.000978 0.002349 0.001664 -0.001318 -0.00139 -0.000712050 0.009607 0.011659 0.004586 0.035115 0.015342 -0.007616 -0.023742 -0.012132


2010 -0.000015 -0.000007 -0.000014 -0.000014 -0.000004 -0.000172 -0.00018 -0.0000922030 -0.000195 -0.000124 -0.000162 -0.000121 -0.000067 -0.002142 -0.003128 -0.0013732050 -0.002242 -0.001455 -0.002026 -0.001154 -0.000009 -0.021133 -0.029887 -0.016601


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1. In some cases GDP and equivalent variation do not move in the same direction, this is due the fact that EV doesn’t take into account capital depreciation, and consequently considers as a positive investment the investment necessary to maintain capital stock at its productive capacity. Moreover EV is related to utility and the functional form used to aggregate utility components transforms considerably these components.

2. As before the variation in CO2 emissions doesn’t have always the same sign of GDP variation. Consider, for instance, developed countries: GDP falls respect to the baseline but CO2 emissions increase. In this case what is highlighted is a substitution process between land and capital. Interestingly this substitution seems particularly strong in developed regions which are relatively capital abundant (USA-EU-Japan-RoA1). On the contrary in developing regions variations in GDP and emissions have the same sign highlighting a weaker substitution possibility between land and capital.

Impact of climate-change induced Impact of climate-change induced sea-level rise: selected resultssea-level rise: selected results

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Implementing Climate-Change Impacts Implementing Climate-Change Impacts on Health and Sea Level Rise in GTAP-EXon Health and Sea Level Rise in GTAP-EX


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Impact of climate change on sea-level Impact of climate change on sea-level rise and health: selected results rise and health: selected results



2010 -0.385192 1.923249 -0.11026 -0.466063 0.550126 -10.86031 -4.043838 -7.6728322030 149.8862 908.5515 80.51505 -11.93361 171.4879 -1197.555 -506.6593 -1189.2192050 -760.7727 2261.295 155.3973 83.19036 885.5419 -5336.194 -2608.251 -5471.128


2010 -0.000008 0.000025 0.000008 -0.000015 0.000026 -0.000265 -0.000258 -0.0001752030 0.001026 0.00569 0.003913 -0.000172 0.005484 -0.019121 -0.016529 -0.0165642050 0.000955 0.013569 0.008301 -0.001374 0.014198 -0.062063 -0.054798 -0.0531


2010 0.000109 0.000141 0.000078 0.000128 0.000133 -0.000178 -0.000094 -0.0000632030 0.002471 0.005071 0.002883 0.003076 0.004626 -0.00914 -0.006795 -0.0062852050 0.010461 0.017709 0.008925 0.030556 0.020502 -0.02736 -0.034161 -0.025516

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Some Limitations Some Limitations

• The choice of modelling the climate change as a one-time event. Climate change occurs progressively over time, and natural systems interact dynamically with human systems.

• On the environmental side, the climate change has its own dynamics, due to the adaptation processes of natural and human systems to the changing environment.

• On the economic side, the static CGE model does not take into account the inter-temporal agents decisions process.


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Future developmentsFuture developments

1. To enlarge the spectrum of climate change effects in the comparative static analysis.

2. To develop the environmental block of equations.

3. To develop a “recursive dynamic” version of the GTAP-E model (GTAP-ER).

4. To have hard-link integration between modules.

evaluating climate change impacts: an integrated approach

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